Abstract
This paper presents an automatic approach which classifies structural Magnetic Resonance images into pathological or healthy controls. A classification model was trained to find the boundaries that allow to separate the study groups. The method uses the deformation values from a set of regions, automatically identified as relevant, in a process that selects the statistically significant regions of a t-test under the restriction that this significance must be spatially coherent within a neighborhood of 5 voxels. The proposed method was assessed to distinguish healthy controls from schizophrenia patients. Classification results showed accuracy between 74% and 89%, depending on the stage of the disease and number of training samples.
| Translated title of the contribution | Automatic classification of structural MRI for diagnosis of neurodegenerative diseases |
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| Original language | Spanish |
| Pages (from-to) | 165-180 |
| Number of pages | 16 |
| Journal | Acta Biologica Colombiana |
| Volume | 15 |
| Issue number | 3 |
| Publication status | Published - Sept 2010 |
| Externally published | Yes |